A new tool called Infrared (IR) imaging technology has been emerging in the field of sports science, providing unique insights into helping athlete with improving their performance, preventing injury and help in adapting with environment by detecting thermal radiation emitted by bodies and objects [1]. It is a non-invasive method that helps to provide a very precise real time monitoring of physiological and environmental conditions which makes it very valuable in sports. Integrating deep learning techniques with infrared imaging helps significantly to enhance the identification of subtle patterns which are present in very large and complicated datasets [2]. This literature review rigorously examines the different applications of infrared imaging in sports, and has classified into these broad categories: performance analysis, injury prevention and management, heat stress monitoring. Taking about performance analysis of players and athletes, it is used for accessing the biomechanical and physiological responses which helps in optimizing the training strategies. In the field of injury prevention and management it is an aid in early detection of injuries and it also helps in injury recovery management. Other than that it also informs game strategies through real-time assessment of opponents’ physical states. This research makes a unique contribution by combining deep learning with infrared imaging, which greatly improves identification and prediction skills for athlete performance, injury risks, and environmental adaption. The goal of the study is to provide fresh perspectives on enhancing athlete well-being and maximizing performance in a range of scenarios by utilizing these technologies. The review highlights the work done in all these broad categories to provide the a systematic review for improving further research in the field of deep learning on infrared images for sports.